{"id":"W4408204264","doi":"10.1093/rsq/hdae024","title":"The Invisibilised Labour of Diasporas as Co-sponsors in Refugee Sponsorship: Lessons <i>From</i> Canada","year":2025,"lang":"en","type":"article","venue":"Refugee Survey Quarterly","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council","keywords":"Refugee; Political science; Business; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008370746,0.0002060819,0.0004085229,0.000140325,0.0005511739,0.0001031795,0.0007232009,0.0001811813,0.0001589787],"category_scores_gemma":[0.001910217,0.0001801448,0.00008951355,0.0009296421,0.0003525492,0.0002224428,0.00001947826,0.0002898154,0.00002939804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003875897,"about_ca_system_score_gemma":0.003216711,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9477628,"about_ca_topic_score_gemma":0.9989195,"domain_scores_codex":[0.9937296,0.004112821,0.0007249955,0.0004303712,0.0004399691,0.0005622245],"domain_scores_gemma":[0.9943054,0.00447275,0.0002670388,0.0005894969,0.0002101587,0.0001550959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001083643,0.0002727265,0.8364346,0.00005741822,0.0001694171,0.00002395877,0.0388821,0.00003095686,0.000265741,0.09824708,0.01292063,0.01161175],"study_design_scores_gemma":[0.0004304689,0.00005993731,0.8822842,0.00004273524,0.000009623969,1.46134e-7,0.007869124,0.000009322684,0.0002074529,0.004532106,0.1043444,0.0002104504],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933138,0.0004624955,0.000009283262,0.002041924,0.0005520411,0.000372967,0.0002786748,0.00003296214,0.002935808],"genre_scores_gemma":[0.9945728,0.0001328643,0.00001490209,0.0003620047,0.00007773466,0.00002763135,0.00005809561,0.00001439727,0.004739598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09371497,"threshold_uncertainty_score":0.7346089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02373175067237929,"score_gpt":0.3245130578591005,"score_spread":0.3007813071867211,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}